JUCESP: Certidão Simplificada

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations provide idempotentHint: true, but the description adds behavioral context by detailing side effects: it can return a login link when called with no args or accept a JWT for session-only login. It clarifies that the token can be stored permanently in config or last only for the session, which goes beyond the annotations without contradicting them.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences long, front-loaded with the core purpose, and provides essential details without unnecessary fluff. A missing newline or bullet list is a minor structural improvement, but it's efficient for the information conveyed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an authentication tool with one optional parameter and no output schema, the description adequately covers usage but omits return value semantics (e.g., success/failure responses) and error scenarios (e.g., invalid token). Given the lack of an output schema, a brief note on expected outcomes would elevate completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema only shows an optional 'token' string with no description (0% coverage). The description fully compensates by explaining that 'token' is a JWT from the user and that omitting it triggers a link generation. This comprehensive explanation makes up for the schema gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool authenticates to MCP.AI for IDE agents by logging in and handling access tokens. It provides specific usage details, distinguishing it from siblings like 'connect' by focusing on token-based authentication. However, it doesn't explicitly contrast with sibling tools, so it misses a top score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context on when to use the tool (for browser-based login to obtain a token) and explains two usage patterns: permanent via config header or session-only via token. It implicitly differentiates by describing the alternative of configuring a header, but doesn't explicitly mention 'use this instead of X'. This is clear enough for a 4.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint:true, idempotentHint:true, and destructiveHint:false. The description adds value by specifying the exact response fields (authenticated, pending) and the presence of connect_url for missing credentials, providing behavioral context beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two concise sentences, front-loaded with the core purpose. It efficiently covers the two main states without unnecessary detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no parameters and no output schema, the description covers the primary outcomes (connected vs missing credentials) sufficiently. It doesn't exhaust all edge cases but is complete enough for the tool's simplicity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With zero parameters, the schema and description need no additional parameter explanation. The schema coverage is effectively 100% (empty object), and the description clarifies the tool's behavior without needing to describe parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns connection status and URLs, and differentiates between fully connected state and missing credentials. It uses specific verbs ('returns') and describes distinct outcomes, distinguishing it from siblings like 'authenticate'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for checking connection status but does not explicitly say when to use this tool versus alternatives. It provides conditional behaviors (all providers connected vs missing credentials) but lacks direct guidance on selection criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover read-only, idempotent, and non-destructive. The description adds valuable behavioral context: payment model, lack of user credentials, sourcing from official government bodies, and LGPD data controller responsibility. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Four concise sentences, each conveying essential information (purpose, hosting/payment, data source, legal responsibility). No fluff, well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 7 parameters and no output schema, the description covers the core use case but omits clarification for credential-related parameters and their optionality, leaving potential confusion. It also doesn't explain the certificate format or detail any response behavior, but that's not strictly required given no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%. Description mentions cnpj, nire, and name as identifiers, but leaves login_cpf, login_senha, pkcs12_cert, and pkcs12_pass unexplained. Also, saying 'sem credenciais' conflicts with the existence of credential parameters, creating ambiguity. The description fails to clarify these parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it issues a simplified business certificate from JUCESP, specifying the resources (CNPJ, NIRE, or name). It's distinct from sibling tools which are platform utilities like authentication and reporting.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear context: hosted platform, no credentials needed, prepaid credits required, and it queries official public data. It implies when to use (for obtaining registration/status proof) but doesn't explicitly state when not to use or alternative tools, though siblings are unrelated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Despite weak annotations (all generic false/true), the description discloses critical behavior: invoke runs tools one-off without installing, writes require workspace owner/admin, connect/checkout link handling and retry, installed_in_toolkit vs installed_in_workspace flags, and the prompt library's public-link behavior. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long (~250 words) but each sentence is information-dense and the structure moves logically from core flow to key invoke behavior, then to install, billing, and prompt library. It could be slightly more streamlined but is appropriate for a complex multi-action tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (14+ actions, 23 params, sub-features like prompt library), the description covers the main flows, edge cases (auth, payment, permissions), and distinctions (permanent vs one-off). There is no output schema, so return values need not be described. It is sufficiently complete for an agent to select and invoke the correct action.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage across 23 params, so the description compensates by explaining the action enum in prose and the essential parameters (mcp_id, tool_id, arguments, action values). However, not all params (e.g., limit, query, immediate, cancel_reason, prompt_vars) are explicitly mapped to their meaning, leaving some inference needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as the official mcp.ai marketplace and the way to run MCPs, with a specific core flow (search → describe → invoke). It distinguishes itself from siblings like report_bug and show_version by outlining the catalog, invocation, and prompt library functions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit guidance throughout: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT', 'If the MCP needs a credential/login, invoke returns a connect link; if paid and wallet empty, invoke returns a checkout link... retry'. Also designates when to use list_tools, request_mcp, subscribe/cancel, and prompt library actions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare idempotentHint=true, destructiveHint=false, and readOnlyHint=false. The description adds the behavioral expectation that the conversation array should be included for reproduction, which is useful context for the agent. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two concise sentences that front-load the purpose and then provide a key usage hint. Every word earns its place with no repetition of the title or annotation metadata.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple reporting tool with no output schema, the description gives a clear purpose and one usage hint, but it omits essential parameter semantics (especially the required message) and introduces a type mismatch for conversation. This leaves the tool only partially complete for an agent to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the burden of explaining parameters. However, it only mentions conversation (one of three params) and inaccurately calls it an 'array' while the schema types it as a string. No explanation of the required 'message' field or optional 'context' field, leaving the agent underinformed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Report a bug, missing feature, or send feedback.' This is a specific verb plus resource, and it is distinct from all sibling tools (authenticate, marketplace, etc.). No ambiguity about what the tool does.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear usage context ('Report a bug...') and provides an explicit how-to instruction ('Include the conversation array with recent messages for reproduction'). It lacks explicit when-not or alternative tool references, but no sibling tool offers similar functionality, so the guidance is sufficient.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description aligns with these and adds no contradicting or missing context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that conveys the tool's purpose without any redundant information. It is well-structured and easy to understand.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of parameters and output schema, the description sufficiently covers what the tool does. No additional context about side effects or return values is necessary.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are no parameters, so the baseline score is 4. The description does not need to explain any parameters, and none are missing.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool shows MCP platform and adapter versions, which is specific and unambiguous. It distinguishes from sibling tools like authentication and connection-related tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The usage is implicitly clear: the tool is used to retrieve version information. No explicit alternatives are needed since it's a simple informational tool, but it lacks explicit 'when not to use' guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare this as read-only, idempotent, and non-destructive. The description adds meaningful behavioral detail by specifying what 'state' means: installed MCPs, connection status, accounts, and catalog tool counts. No contradictions found.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that front-loads the purpose and lists the key output categories. Every clause contributes meaning with no redundant wording.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a parameterless, read-only status tool, the description fully covers the tool's behavior and output categories. No output schema is present, but the enumerated return contents provide sufficient completeness for an agent to decide whether to call it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so there is no parameter semantics to explain. The baseline of 4 is appropriate because the description accurately communicates that the tool takes no input and simply returns state.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Returns') and clearly identifies the resource: current toolkit state. It enumerates exactly what is included (installed MCPs, connection status, connected accounts, catalog tool counts), which differentiates it from sibling tools like connect or authenticate.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies this is the appropriate tool for inspecting toolkit status or troubleshooting connectivity, as opposed to performing actions like connect or authenticate. It provides clear context but does not explicitly state when not to use it or name alternative tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.